Multi-layer system capacity planning

ABSTRACT

A software-defined network multi-layer controller (SDN-MLC) may communicate with multiple layers of a telecommunication network. The SDN-MLC may have an optimization algorithm that helps in capacity planning of the telecommunications based on the management of multiple layers of the telecommunication network.

BACKGROUND

A packet layer of the network may include internet protocol (IP) linksconnected among IP devices such as router ports. The IP links may berouted over a path in the optical layer and use reconfigurable opticaladd-drop multiplexers (ROADMs) and transponders at the endpoints, andoptical signal regenerators (or repeaters) in the middle of the pathwhen the path is longer than the optical reach. A transponder is anintermediary between the IP and the optical layers of the network and isused to perform electrical-to-optical conversion andoptical-to-electrical conversion. A connected combination of a IP portand a transponder is defined as a “Tail” . . . IP ports, opticaltransponders, and optical regenerators are typically associated with acertain bandwidth unit such as 40 Gbps, 100 Gbps, 200 Gbps, or 400 Gbps.If there are N traffic endpoints and K Quality of Service (QoS) classesthen the traffic matrix consists of K*N*(N−1) individual traffic units,all of which may change over time. This disclosure is directed toaddressing issues in the existing technology.

SUMMARY

Disclosed herein are techniques that may address repeated joint globaloptimization (e.g., whenever network condition changes) while running amulti-layer network. These network condition changes may be based ontraffic matrix changes, scheduled outages (e.g., maintenance activitysuch as software upgrades) or unscheduled outages (e.g., caused by fibercuts or failure of IP or optical devices). A software-defined networkmulti-layer controller (SDN-MLC) may communicate with multiple layers ofa telecommunication network. The SDN-MLC may have an optimizationalgorithm that helps manage, in near real-time, the multiple layers ofthe telecommunication network. Joint multi-layer global optimization maybe used to respond to network condition changes caused by traffic matrixchanges, scheduled outages, or unscheduled outages. Near real-timeoptimization makes the best use of available capacity installed in thenetwork. However, over time the installed capacity may not be sufficientto meet the quality of service requirements. Multilayer capacityplanning provides an optimal (e.g., minimum) estimate of needs for IPcapacity or optical capacity in order to ensure that a network hasenough resources for some specified period of time in the future (e.g.,days, weeks, or months).

In an example, an apparatus (e.g., software-defined network controller)may include a processor and a memory coupled with the processor thateffectuates operations. The operations may include: obtaining multiplelayer information associated with multiple layers of atelecommunications network, the multiple layer information comprisingoptical layer information and router layer information; based on themultiple layer information, forecasting operation of thetelecommunications network for a plurality of network conditions; basedon the forecasted operations of the telecommunication network for theplurality of network conditions, providing a capacity plan option forthe telecommunications network. The configuration change of thecomponent of the router layer may include a routing path of traffic in arouting table. The configuration change (e.g., capacity action) may beaddition of a router card, optical regenerator, or transponder.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used to limit the scope of the claimed subject matter. Furthermore,the claimed subject matter is not limited to limitations that solve anyor all disadvantages noted in any part of this disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

Reference will now be made to the accompanying drawings, which are notnecessarily drawn to scale.

FIG. 1A illustrates an exemplary system for managing multi-layerself-optimization.

FIG. 1B illustrates FIG. 1A in further detail.

FIG. 2 illustrates an exemplary method for managing multi-layer systemself-optimization.

FIG. 3 illustrates an exemplary method for capacity planning or managingmulti-layer system self-optimization.

FIG. 4 illustrates an exemplary method for capacity planning or managingmulti-layer system self-optimization.

FIG. 5 illustrates a schematic of an exemplary network device.

FIG. 6 illustrates an exemplary communication system that provideswireless telecommunication services over wireless communicationnetworks.

FIG. 7 is a representation of an exemplary network.

DETAILED DESCRIPTION

Conventional approaches to network optimization and planning may assumethat the mapping between an IP link and the set of optical transpondersand regenerators needed underneath is fixed and if any component fails,the entire IP link fails and the non-failed components of the IP linkare rendered unusable. Also, conventional approaches may assumeconsideration of traffic routing over the IP layer and the optical layerseparately. Conventionally, optical layer optimization (e.g., the choiceof IP links and their mapping over the optical layer) may rarely be done(e.g., once) and when optical layer optimization is done it is usuallywith a consideration that the IP layer traffic should only be routedover these once-determined set of IP links. Again, due to lack of jointglobal optimization of IP and optical layers, conventional approachesuse significantly more IP resources and optical resources.

Disclosed herein are techniques that may address repeated joint globaloptimization (whenever network condition changes) while operating amulti-layer network. These network condition changes may be based ontraffic changes (e.g., spike in traffic to an internet resource becauseof an emergency, holiday, or media event (e.g., promotion a associatedwith a website), scheduled outages (e.g., maintenance activity such assoftware upgrades), or unscheduled outages (e.g., caused by fiber cutsor failure of IP or optical devices). For capacity planning purposesthere may be repeated joint global multi-layer optimization forcomputing required IP/Optical resources (IP ports, optical transponders,or optical regenerators) to cover traffic matrix and outage scenariosover a specified period of time in the future (e.g., days, weeks, ormonths), while satisfying engineering rules (e.g., percentage of trafficof various types that should be carried plus certain latency constraintsthat should be met).

FIG. 1A illustrates an exemplary system for multi-layerself-optimization. Software-defined network multi-layer controller 112(SDN-MLC 112) may communicate with multiple layers of system 100 (e.g.,a telecommunication network). SDN-MLC 112 may have an optimizationalgorithm that helps manage multiple layers of the network. The multiplelayers may include optical layer 150, router layer 130 (which may alsobe a switch layer), and multi-protocol label switching (MPLS) tunnelinglayer 120. As generally shown in FIG. 1A (and with more detail in FIG.1B), there may be multiple sites, which include one or more componentsthat help build one or more physical or logical connections. Forexample, in FIG. 1B, for site 101 it may include router 131, tail 161,ROADM 151, or regenerator 171 of FIG. 1B). FIG. 1A illustratesconnections between multiple sites as may be seen at each level. Sitesinclude site 101 through site 109. Some sites (e.g., site 107) may haveoptical equipment (ROADM 157), but may not have routing equipment.

FIG. 1B illustrates FIG. 1A in further detail. Optical layer 150 mayinclude multiple components, such as reconfigurable optical add-dropmultiplexer (ROADMs) (e.g., ROADM 151-ROADM 159), tails (e.g., tail161-tail 168), and regenerators (e.g., regenerator 171-regenerator 178).A ROADM is a form of optical add-drop multiplexer that adds the abilityto remotely switch traffic from a wavelength-division multiplexing (WDM)system at the wavelength layer. A tail is a connection between aninternet protocol (IP) port (e.g., port of router 131) and a transponderport (e.g., port of transponder 181). In optical fiber communications, atransponder is the element that sends and receives the optical signalfrom a fiber. A transponder is typically characterized by its data rateand the maximum distance the signal can travel. An opticalcommunications regenerator may be used in a fiber-optic communicationssystem to regenerate an optical signal. Such regenerators may be used toextend the reach of optical communications links by overcoming loss dueto attenuation of the optical fiber. Some regenerators may also correctfor distortion of the optical signal by converting it to an electricalsignal, processing that electrical signal, and then retransmitting anoptical signal. Router layer 130 may include routers (e.g., router131-router 136) or switches (not shown). MPLS layer 120 may have severaltunnels logically connected via the routers in router layer 130.

FIG. 2 illustrates an exemplary method for multi-layer capacityplanning. In an exemplary scenario, as shown in FIG. 1A and FIG. 1B,there may be a system 100 with an optical layer 150, router layer 130,and a MPLS layer 120. At step 191, information about each layer may beobtained, which may be over days, weeks, months, or more. Thisinformation may be before, during, or subsequent to an outage or otherevent of system 100 and may be used for forecasting. The information mayassist in understanding activity patterns for system 100. For example,activity patterns (which may include scheduled or unscheduled outages)may include the frequency of network link outages (and flow of trafficactivity thereafter), dates and times of significant traffic load onsystem 100, minimum or maximum average (or median) traffic load onsystem 100 during a period, traffic matrix changes, trouble tickets(outages may be experienced by users, but not detected through normaltechniques), or estimated time of repair on a layer (which may be basedon similar errors, alarms, or diagnosed issues), among other things.Information may be gathered on each layer. For MPLS layer 120, theinformation may include the MPLS interface state, reserved bandwidth, orlabel switching paths, among other things. For router layer 130, theremay be information that includes input bytes, output bytes, inputpackets, output packets, input errors, input drops, input framingerrors, output errors, output drops, usual traffic load on affectedlink, types of traffic on affected link (e.g., defined QoS, video,voice, TCP, UDP, source address, etc.), or routing information, amongother things. The router layer information may be obtained from one ormore routers. For optical layer 150, the information may includelocation of optical equipment (e.g., transponder 181, regen 171, ROADM157, or tails), errors from the optical equipment, length of opticalpaths, or outages of the optical equipment, among other things. Theoptical layer information may be obtained from one more ROADMs.

With continued reference to FIG. 2, based on multi-layer information ofstep 192 (e.g., optical layer and router layer information), there is adetermination whether a change short-term or intermediate-term change inconfiguration of existing capacity of the optical layer or router layermay resolve undesirable network conditions alerted to by the information(e.g., information of step 191). A resolution may be based on apredetermined period and predetermined engineering (or the like)thresholds. The period would usually range from days to weeks or months.The predetermined engineering thresholds may include service levelagreements (SLAs) for transport for much of the information of step 191,such as errors, traffic loads, or types of traffic, among other things.For example, in this scenario, the load along an optical path site101-107-106-104 (i.e., path 11) may have reached a threshold (e.g., 80percent) during a period (e.g., 30 minute time frame), which may causeerrors or latency. A first selected option may be for ROADMs along thepath (e.g., ROADM 151, ROADM 157, ROADM 156, and ROADM 154) to add onemore wavelengths carrying data channels to increase the capacity alongpath 11. This may be preferred over changing a routing path at routinglayer 130, because there may be a tendency for the routing protocol tosend traffic through router path site 105-104, which actual goes overoptical path site 106-104 and doesn't help resolve the congestion. Oralternatively, it may be selected because SDN-MLC 112 may constantlyhave to adjust the routing metrics, which may cause high utilization(e.g., eventually slow response) of SDN-MLC 112, or it may be selectedbecause routing changes would have a service fall outside its SLA.

A second selected option (at a different time with different weightedinfo) may be for just the router layer 120 to be changed. Routes to someor all the traffic may be weighted to go through one or more routers(e.g., router 132) of site 102, because optical path site102-103-109-104 does not go through optical path site 106-104. Anadditional consideration that may have led for this second selectionoption may be that the ROADMs could not (e.g., no more channelsavailable) or should not increase its wavelength based on theinformation as disclosed in step 191. A third selected option (at yet adifferent time with different weighted info) may decide to do acombination of router layer 130 and optical layer 150 solutions (e.g.,configuration changes) in order to reduce the traffic to an acceptablethreshold (e.g., 30 percent). For instance, traffic for a couple ofheavy users along the path may be redirected and stay within SLAs, whilean increase in ROADM may be enough to accommodate the traffic load basedon information of other users. SDN-MLC 112 may be used to determine thechange needed in this step 192.

With reference to step 192, it may have sub-divided steps for capacityplanning. For example, there may be a determination of somewhatimmediate (e.g., near real-time) changes to configurations that may becommunicated to router layer 130 or optical layer 150 devices. There mayalso be a consideration of the different parts within system 100 (e.g.,see FIG. 3) that may not be automatically or immediately changed, butwould provide capacity (for example) that would address issuesdetermined by analyzing the information of step 191 or the like. Asshown, SDN-MLC 112 may obtain data from different sources, such as taildatabase 114, that allows SDN-MLC 112 to know the current usage ofrouter layer 130 components or optical layer 150 components. If aregenerator, ROADM, tail, or the like are not in use (e.g., because ofre-provisioned customer service) or can be added to system 100 to extendthe period to be within the predetermined engineering thresholds, thenSDN-MLC may automatically order the component or provide an alert (e.g.,via a display) regarding the component to be authorized and ordered by auser.

With continued reference to step 192, as disclosed herein, optimalestimate may consider the lowest capital cost but yet the estimation maysatisfy both no-fail scenario and a specified set of failure scenariosand under each such scenario it should satisfy a specified set ofengineering rule constraints (e.g., percentage of traffic of each typeto be carried and latency constraints). Again, due to lack of jointglobal optimization of IP and optical layers, conventional approachesused significantly more IP resources and optical resources.

At step 193, SDN-MLC 112 may provide instructions based on thedetermination of step 192. For example, SDN-MLC 112 may communicate withrouters, ROADMs, tails, ordering system 115, ROADM SDN controller 110,or the like to execute the determination of step 192. ROADM SDNcontroller 110 may be an intermediate device that may directlycommunicate with optical layer 150 devices. Ordering system 115 may beused to order one or more devices for future use (e.g., spare). Theremay be an anticipated need for the spare based on the information ofstep 191. At this step, SDN-MLC 112 may provide one or more capacityplanning options for system 100. The capacity planning options may beadding/removing/repurposing/stocking spares of one or more components,such as router, router ports, tails, ROADMs, or other router layer, MPLSlayer, or optical layer components.

SDN-MLC 112 may manage the multiple layers of system 100 in a closedloop and heuristic manner. In a first example, this management may allowfor dynamic mapping between a router layer and an optical layer by usingcolorless or directionless open ROADMs and reusing non-failed routerlayer or optical layer components of a failed link. In a second example,this management may allow for the use of spare tails (connection betweena router port and optical transponder port) and spare opticalregenerators. In a third example, this management by SDN-MLC 112 mayallow router layer devices to be physical or virtual and software andhardware to be aggregated (e.g., traditional routers) or dis-aggregated(e.g., whitebox switches).

Based on the network condition (e.g., traffic matrix or outages)changes, the mapping between IP (e.g., router) and optical layers may bechanged to more efficiently carry traffic under the changed networkcondition. Joint optimization of IP and optical layers whenever thenetwork condition changes may be done by using algorithms based oninteger linear programming or heuristics.

FIG. 3 illustrates an exemplary method for capacity planning inmulti-layer systems as disclosed herein. At step 201, initially system100 may include unconnected sets of tails and regenerators. Each suchtail and optical regenerator may be classified as spare tails and spareoptical regenerators. For a given network condition, only a selectedsubset of spare tail pairs may be connected to form an IP link thatcarries the required traffic (e.g., less than 70 percent load) under therequired latency constraints (e.g., 5 ms). Depending on the length(e.g., in miles) of a specific IP link, it may require spare opticalregenerators as well. At step 202, a joint multi-layer globaloptimization may be done to choose the right set of spare tail pairs(plus optical regenerators, if needed) along with the proper IP layerrouting. The joint optimization should satisfy engineering ruleconstraints (e.g., percentage of traffic of each type to be carried andlatency constraints), use realizable routing (e.g., shortest pathrouting, constrained shortest path routing, multi-commodity flow routingwith the restriction of equal splitting of traffic units, etc.), oroptimize some other desirable quantities (e.g., maximizing unused sparetails and regenerators, minimizing the maximum traffic on a link, etc.).At step 203, SDN-MLC 112 may provide instructions for IP devices (e.g.,physical or virtual routers) or optical layer devices to be turned up ordown depending on network conditions of system 100.

With continued reference to FIG. 3, at step 204, there may be a detectedchange in network condition that may result in a change in the trafficmatrix and a certain set of tails and regenerators to fail, oralternatively some previously failed tails and regenerators may becomeoperational. At step 205, taking account of the traffic and failureconditions, a new joint multi-layer global optimization may beperformed. The new joint multi-layer global optimization may result insome previously established IP links to be taken down and some new IPlinks to be added and thus also reflecting the dynamic nature andcontrol of the network topology. The joint global optimization problemmay be formulated as an exact integer linear programming problem, but ifthe exact algorithm is time consuming then a fast heuristic may be used.At step 206, SDN-MLC 112 may provide instructions for IP devices (e.g.,physical or virtual) or optical layer devices to be turned up or downdepending on network conditions of system 100. Software or hardware mayremain aggregated or may be disaggregated.

FIG. 4 illustrates another exemplary method for capacity planning formulti-layer systems as disclosed herein. The main capacity units used tooptimize over are the tails and regenerators where a tail includes an IPport and a transponder. Let C1 and C2 represent the costs of a tail anda regenerator respectively, and N1 and N2 represent the numbers of tailsand regenerators needed in the final solution. The quantity(C1*N1+C2*N2) is optimized over the possible network change scenarios.At step 211, the number of tails are set to zero. Initially the networkmay only include zero tails and zero regenerators. At step 212, for onegiven network change condition, minimum set of tails and regeneratorsmay be selected that can be connected appropriately to form IP linksthat can carry the required traffic under the required engineering ruleconstraints. At step 213, the analysis of significant number of networkchange conditions may be repeated. This selection may be based onanalysis of many different traffic scenarios and different failurescenarios. Preferably, all the different combination are analyzed. Forexample, repeated may be similar to the following: 1). Peak traffic onday 1; 2) Peak traffic on day 2; 3) Day 1, but some of the links/routershave failed—with same traffic load for day 1, etc. For any given networkchange condition, tails and regenerators used for previous networkchange conditions may be considered for reuse. The joint globaloptimization problem over the several network change scenarios can beformulated as an exact integer linear programming problem, but if theexact algorithm is time consuming then a fast heuristic may be used. Atstep 214, SDN-MLC 112 implements or provides options (e.g., displays)for implementing one or more capacity plans. The capacity planningactions may be adding/removing/repurposing/stocking spares of one ormore components, such as router, router ports, tails, ROADMs, or otherrouter layer, MPLS layer, or optical layer components.

The disclosed capacity planning approach may anticipate all failure andtraffic surge scenarios over the next few weeks or months and for eachscenario may consider a joint router layer or optical layer globaloptimization to minimize the total cost of tails, regenerators, or otherdevices. The disclosed methods, systems, and apparatuses may provide anoptimal network that results in network capex savings in the range of15-30% or more. Table 1 helps illustrate an example with the componentsof cost that may include router IP port, optical transponder, or opticalregenerator. For this example, note that Tail=Packet Port+Transponder;traffic Numbers are provided for exemplary purpose only; Costassumptions are: 1) optical regenerator cost ˜1.5*Transponder cost; and2) router port cost ˜2.5*Transponder cost. The normalized cost is inunits of transponder cost for this example. As shown, there is potentialfor ˜34% CAPEX cost saving with joint global optimization.

TABLE 1 # of 100 # of 100 Normalized Scenario GE Tails GE Regens CostPMO 1153 226 2105 +Fast Provisioning 1048 105 1913 (−9%) +JointOptimization 939 91 1711 (−18.5%) on Existing Links +Joint Global 740130 1392 (−34%) Optimization (add links anywhere)

Although a router layer, optical layer, and MPLS tunneling layer arediscussed, it is contemplated that the MPLS tunneling layer be someother tunneling layer or not present at all. Also, it is contemplatedthat the optical layer may be another physical layer other than optical.As discussed herein, the router layer, may be a switching layer or thelike. It is contemplated herein that the term information as consideredherein may be information on any layer (e.g., layer 130 or layer 150).Activity patterns as disclosed herein may be considered “information”which is used in step 192. Whether an outage is scheduled or unscheduledis other information that may be used for determining capacity planning.With reference to estimated time for repair, it is contemplated thatsometimes it may take less time to implement a router layer solutionrather than an optical layer solution (or vice versa). Although time maybe a significant factor, SDN-MLC 112 may consider a predetermined weightof the information in order to derive a weighted determination (e.g.,step 192 or step 202). The disclosed techniques may be used to helpchange the amount of capacity units (e.g., devices and connectionconfigurations) in different layers of the network so that nearreal-time optimization has sufficient installed resources to meet thequality of service requirements of the network.

Disclosed herein is capacity planning as an option on the SDNcontroller. There may also be standalone capacity planning system thatuses the same data and potentially the same core optimization algorithm.Again, disclosed is capacity planning which may be over a set futuretime period (that can be days, weeks or months) which basicallyidentifies how much additional resources would be needed over that setfuture time period in addition to what is already in the definedtelecommunications network. Using observation of past traffic patternsplus forecasting of traffic growth, identified herein may be a set oftraffic matrix conditions and failure conditions that can be realizedover the set future time period. Each traffic matrix condition andfailure condition may be simulated one at a time and using jointmulti-layer optimization for that condition that identifies how muchadditional resources (e.g., Tails+Regens) on top of current resourcesmay be needed to satisfy each traffic matrix condition and failurecondition. There may be a final determination of the minimal amount ofadditional resources needed to satisfy every traffic matrix conditionand failure condition.

FIG. 5 is a block diagram of network device 300 that may be connected toor comprise a component of system 100 of FIG. 1A. Network device 300 maycomprise hardware or a combination of hardware and software. Thefunctionality to facilitate telecommunications via a telecommunicationsnetwork may reside in one or combination of network devices 300. Networkdevice 300 depicted in FIG. 5 may represent or perform functionality ofan appropriate network device 300, or combination of network devices300, such as, for example, a component or various components of acellular broadcast system wireless network, a processor, a server, agateway, a node, a mobile switching center (MSC), a short messageservice center (SMSC), an automatic location function server (ALFS), agateway mobile location center (GMLC), a radio access network (RAN), aserving mobile location center (SMLC), or the like, or any appropriatecombination thereof. It is emphasized that the block diagram depicted inFIG. 5 is exemplary and not intended to imply a limitation to a specificimplementation or configuration. Thus, network device 300 may beimplemented in a single device or multiple devices (e.g., single serveror multiple servers, single gateway or multiple gateways, singlecontroller or multiple controllers). Multiple network entities may bedistributed or centrally located. Multiple network entities maycommunicate wirelessly, via hard wire, or any appropriate combinationthereof.

Network device 300 may comprise a processor 302 and a memory 304 coupledto processor 302. Memory 304 may contain executable instructions that,when executed by processor 302, cause processor 302 to effectuateoperations associated with mapping wireless signal strength. As evidentfrom the description herein, network device 300 is not to be construedas software per se.

In addition to processor 302 and memory 304, network device 300 mayinclude an input/output system 306. Processor 302, memory 304, andinput/output system 306 may be coupled together (coupling not shown inFIG. 5) to allow communications between them. Each portion of networkdevice 300 may comprise circuitry for performing functions associatedwith each respective portion. Thus, each portion may comprise hardware,or a combination of hardware and software. Accordingly, each portion ofnetwork device 300 is not to be construed as software per se.Input/output system 306 may be capable of receiving or providinginformation from or to a communications device or other network entitiesconfigured for telecommunications. For example input/output system 306may include a wireless communications (e.g., 3G/4G/GPS) card or wiredcommunications (e.g. optical lines) card. Input/output system 306 may becapable of receiving or sending video information, audio information,control information, image information, data, or any combinationthereof. Input/output system 306 may be capable of transferringinformation with network device 300. In various configurations,input/output system 306 may receive or provide information via anyappropriate means, such as, for example, optical means (e.g., infrared),electromagnetic means (e.g., RF, Wi-Fi, Bluetooth®, ZigBee®), acousticmeans (e.g., speaker, microphone, ultrasonic receiver, ultrasonictransmitter), or a combination thereof.

Input/output system 306 of network device 300 also may contain acommunication connection 308 that allows network device 300 tocommunicate with other devices, network entities, or the like.Communication connection 308 may comprise communication media.Communication media typically embody computer-readable instructions,data structures, program modules or other data in a modulated datasignal such as a carrier wave or other transport mechanism and includesany information delivery media. By way of example, and not limitation,communication media may include wired media such as a wired network ordirect-wired connection, or wireless media such as acoustic, RF,infrared, or other wireless media. The term computer-readable media asused herein includes both storage media and communication media.Input/output system 306 also may include an input device 310 such askeyboard, mouse, pen, voice input device, or touch input device.Input/output system 306 may also include an output device 312, such as adisplay, speakers, or a printer.

Processor 302 may be capable of performing functions associated withtelecommunications, such as functions for processing broadcast messages,as described herein. For example, processor 302 may be capable of, inconjunction with any other portion of network device 300, determining atype of broadcast message and acting according to the broadcast messagetype or content, as described herein.

Memory 304 of network device 300 may comprise a storage medium having aconcrete, tangible, physical structure. As is known, a signal does nothave a concrete, tangible, physical structure. Memory 304, as well asany computer-readable storage medium described herein, is not to beconstrued as a signal. Memory 304, as well as any computer-readablestorage medium described herein, is not to be construed as a transientsignal. Memory 304, as well as any computer-readable storage mediumdescribed herein, is not to be construed as a propagating signal. Memory304, as well as any computer-readable storage medium described herein,is to be construed as an article of manufacture.

Memory 304 may store any information utilized in conjunction withtelecommunications. Depending upon the exact configuration or type ofprocessor, memory 304 may include a volatile storage 314 (such as sometypes of RAM), a nonvolatile storage 316 (such as ROM, flash memory), ora combination thereof. Memory 304 may include additional storage (e.g.,a removable storage 318 or a non-removable storage 320) including, forexample, tape, flash memory, smart cards, CD-ROM, DVD, or other opticalstorage, magnetic cassettes, magnetic tape, magnetic disk storage orother magnetic storage devices, USB-compatible memory, or any othermedium that can be used to store information and that can be accessed bynetwork device 300. Memory 304 may comprise executable instructionsthat, when executed by processor 302, cause processor 302 to effectuateoperations to map signal strengths in an area of interest.

FIG. 6 depicts an exemplary diagrammatic representation of a machine inthe form of a computer system 500 within which a set of instructions,when executed, may cause the machine to perform any one or more of themethods described above. One or more instances of the machine canoperate, for example, as processor 302, router 131, and other devices ofFIG. 1A, FIG. 1B, and FIG. 7. In some embodiments, the machine may beconnected (e.g., using a network 502) to other machines. In a networkeddeployment, the machine may operate in the capacity of a server or aclient user machine in a server-client user network environment, or as apeer machine in a peer-to-peer (or distributed) network environment.

The machine may comprise a server computer, a client user computer, apersonal computer (PC), a tablet, a smart phone, a laptop computer, adesktop computer, a control system, a network router, switch or bridge,or any machine capable of executing a set of instructions (sequential orotherwise) that specify actions to be taken by that machine. It will beunderstood that a communication device of the subject disclosureincludes broadly any electronic device that provides voice, video ordata communication. Further, while a single machine is illustrated, theterm “machine” shall also be taken to include any collection of machinesthat individually or jointly execute a set (or multiple sets) ofinstructions to perform any one or more of the methods discussed herein.

Computer system 500 may include a processor (or controller) 504 (e.g., acentral processing unit (CPU)), a graphics processing unit (GPU, orboth), a main memory 506 and a static memory 508, which communicate witheach other via a bus 510. The computer system 500 may further include adisplay unit 512 (e.g., a liquid crystal display (LCD), a flat panel, ora solid state display). Computer system 500 may include an input device514 (e.g., a keyboard), a cursor control device 516 (e.g., a mouse), adisk drive unit 518, a signal generation device 520 (e.g., a speaker orremote control) and a network interface device 522. In distributedenvironments, the embodiments described in the subject disclosure can beadapted to utilize multiple display units 512 controlled by two or morecomputer systems 500. In this configuration, presentations described bythe subject disclosure may in part be shown in a first of display units512, while the remaining portion is presented in a second of displayunits 512.

The disk drive unit 518 may include a tangible computer-readable storagemedium 524 on which is stored one or more sets of instructions (e.g.,software 526) embodying any one or more of the methods or functionsdescribed herein, including those methods illustrated above.Instructions 526 may also reside, completely or at least partially,within main memory 506, static memory 508, or within processor 504during execution thereof by the computer system 500. Main memory 506 andprocessor 504 also may constitute tangible computer-readable storagemedia.

FIG. 7 is a representation of an exemplary network 600 (e.g., cloud).Network 600 (e.g., system 100) may comprise an SDN—that is, network 600may include one or more virtualized functions implemented on generalpurpose hardware, such as in lieu of having dedicated hardware for everynetwork function. That is, general purpose hardware of network 600 maybe configured to run virtual network elements to support communicationservices, such as mobility services, including consumer services andenterprise services. These services may be provided or measured insessions.

A virtual network functions (VNFs) 602 may be able to support a limitednumber of sessions. Each VNF 602 may have a VNF type that indicates itsfunctionality or role. For example, FIG. 7 illustrates a gateway VNF 602a and a policy and charging rules function (PCRF) VNF 602 b.Additionally or alternatively, VNFs 602 may include other types of VNFs.Each VNF 602 may use one or more virtual machines (VMs) 604 to operate.Each VM 604 may have a VM type that indicates its functionality or role.For example, FIG. 7 illustrates a management control module (MCM) VM 604a, an advanced services module (ASM) VM 604 b, and a DEP VM 604 c.Additionally or alternatively, VMs 604 may include other types of VMs.Each VM 604 may consume various network resources from a hardwareplatform 606, such as a resource 608, a virtual central processing unit(vCPU) 608 a, memory 608 b, or a network interface card (NIC) 608 c.Additionally or alternatively, hardware platform 606 may include othertypes of resources 608.

While FIG. 7 illustrates resources 608 as collectively contained inhardware platform 606, the configuration of hardware platform 606 mayisolate, for example, certain memory 608 c from other memory 608 c.

As described herein, a telecommunications system wherein management andcontrol utilizing a software defined network (SDN) and a simple IP arebased, at least in part, on user equipment, may provide a wirelessmanagement and control framework that enables common wireless managementand control, such as mobility management, radio resource management,QoS, load balancing, etc., across many technologies; decoupling themobility control from data planes to let them evolve and scaleindependently; reducing network state maintained in the network based onuser equipment types to reduce network cost and allow massive scale;shortening cycle time and improving network upgradability; flexibilityin creating end-to-end services based on types of user equipment andapplications, thus improve customer experience; or improving userequipment power efficiency and battery life—especially for simple M2Mdevices—through enhanced wireless management.

Crossing or meeting a threshold as discussed herein, which may triggerthe determining step 192, may be described as surpassing a number thatis prescribed in order to determine when some action is triggered. Forexample, a threshold may be crossed if the number of keepalives from adevice is below a certain amount (e.g., 3) within a timeframe (e.g., 10minutes) and therefore an alert may be triggered. In another example, athreshold may be crossed if the number of errors is above a certainamount (e.g., 100) within a certain time frame (e.g., 1 minute) andtherefore an alert may be triggered.

While examples of a telecommunications system in which multi-layerself-optimization may be processed and managed have been described inconnection with various computing devices/processors, the underlyingconcepts may be applied to any computing device, processor, or systemcapable of facilitating a telecommunications system. The varioustechniques described herein may be implemented in connection withhardware or software or, where appropriate, with a combination of both.Thus, the methods and devices may take the form of program code (i.e.,instructions) embodied in concrete, tangible, storage media having aconcrete, tangible, physical structure. Examples of tangible storagemedia include floppy diskettes, CD-ROMs, DVDs, hard drives, or any othertangible machine-readable storage medium (computer-readable storagemedium). Thus, a computer-readable storage medium is not a signal. Acomputer-readable storage medium is not a transient signal. Further, acomputer-readable storage medium is not a propagating signal. Acomputer-readable storage medium as described herein is an article ofmanufacture. When the program code is loaded into and executed by amachine, such as a computer, the machine becomes an device fortelecommunications. In the case of program code execution onprogrammable computers, the computing device will generally include aprocessor, a storage medium readable by the processor (includingvolatile or nonvolatile memory or storage elements), at least one inputdevice, and at least one output device. The program(s) can beimplemented in assembly or machine language, if desired. The languagecan be a compiled or interpreted language, and may be combined withhardware implementations.

The methods and devices associated with a telecommunications system asdescribed herein also may be practiced via communications embodied inthe form of program code that is transmitted over some transmissionmedium, such as over electrical wiring or cabling, through fiber optics,or via any other form of transmission, wherein, when the program code isreceived and loaded into and executed by a machine, such as an EPROM, agate array, a programmable logic device (PLD), a client computer, or thelike, the machine becomes an device for implementing telecommunicationsas described herein. When implemented on a general-purpose processor,the program code combines with the processor to provide a unique devicethat operates to invoke the functionality of a telecommunicationssystem.

While a telecommunications system has been described in connection withthe various examples of the various figures, it is to be understood thatother similar implementations may be used or modifications and additionsmay be made to the described examples of a telecommunications systemwithout deviating therefrom. For example, one skilled in the art willrecognize that a telecommunications system as described in the instantapplication may apply to any environment, whether wired or wireless, andmay be applied to any number of such devices connected via acommunications network and interacting across the network. Therefore, atelecommunications system as described herein should not be limited toany single example, but rather should be construed in breadth and scopein accordance with the appended claims.

In describing preferred methods, systems, or apparatuses (e.g., devices)of the subject matter of the present disclosure—multi-layer capacityplanning—as illustrated in the Figures, specific terminology is employedfor the sake of clarity. The claimed subject matter, however, is notintended to be limited to the specific terminology so selected, and itis to be understood that each specific element includes all technicalequivalents that operate in a similar manner to accomplish a similarpurpose. In addition, the use of the word “or” is generally usedinclusively unless otherwise provided herein. Real-time as discussedherein refers to operations that usually occur in seconds, but not morethan a minute. As disclosed herein, near real-time events usually occurwithin minutes. A traffic matrix may represent the load from eachingress point to each egress point in an IP network. Although networksare engineered to tolerate some variation in the traffic matrix, largechanges may lead to congested links and poor performance. Configurationchange of a component as disclosed herein may include a software changeor a hardware change (e.g., replace or remove).

This written description uses examples to enable any person skilled inthe art to practice the claimed invention, including making and usingany devices or systems and performing any incorporated methods. Thepatentable scope of the invention is defined by the claims, and mayinclude other examples that occur to those skilled in the art (e.g.,skipping steps, combining steps, or adding steps between exemplarymethods disclosed herein). Such other examples are intended to be withinthe scope of the claims if they have structural elements that do notdiffer from the literal language of the claims, or if they includeequivalent structural elements with insubstantial differences from theliteral languages of the claims.

What is claimed:
 1. An apparatus comprising: a processor; and a memorycoupled with the processor, the memory storing executable instructionsthat when executed by the processor cause the processor to effectuateoperations comprising: obtaining multiple layer information associatedwith multiple layers of a telecommunications network, the multiple layerinformation comprising optical layer information and router layerinformation; based on the multiple layer information, forecastingoperation of the telecommunications network for a plurality of networkconditions; and based on the forecasted operations of thetelecommunication network for the plurality of network conditions,providing a capacity plan option for the telecommunications network. 2.The apparatus of claim 1, wherein the capacity plan option is furtherbased on a maximum capital expenditure for the configuration change. 3.The apparatus of claim 1, wherein the capacity plan option comprisesaddition of a router card.
 4. The apparatus of claim 1, wherein thecapacity plan option comprises an addition of a tail.
 5. The apparatusof claim 1, wherein the capacity plan option comprises an addition of anoptical regenerator.
 6. The apparatus of claim 1, wherein the capacityplan option is further based on a service level agreement for theconfiguration change.
 7. The apparatus of claim 1, wherein the capacityplan option comprises an addition of a wavelength channel of areconfigurable optical add-drop multiplexer.
 8. The apparatus of claim1, wherein the optical layer information comprises an outage alarm. 9.The apparatus of claim 1, wherein the optical layer informationcomprises a load along an optical path.
 10. A method comprising:obtaining, by a device, multiple layer information associated withmultiple layers of a telecommunications network, the multiple layerinformation comprising optical layer information and router layerinformation; based on the multiple layer information, forecasting, bythe device, operation of the telecommunications network for a pluralityof network conditions; and based on the forecasted operations of thetelecommunication network for the plurality of network conditions,providing, by the device, a capacity plan option for thetelecommunications network.
 11. The method of claim 10, wherein thecapacity plan option is further based on a maximum capital expenditurefor the configuration change.
 12. The method of claim 10, wherein thecapacity plan option comprises addition of a router card.
 13. The methodof claim 10, wherein the capacity plan option comprises an addition of atail.
 14. The method of claim 10, wherein the capacity plan optioncomprises an addition of an optical regenerator.
 15. The method of claim10, wherein the capacity plan option is further based on a service levelagreement for the configuration change.
 16. The method of claim 10,wherein the capacity plan option comprises an addition of a wavelengthchannel of a reconfigurable optical add-drop multiplexer.
 17. The methodof claim 10, wherein the optical layer information comprises an outagealarm.
 18. The method of claim 10, wherein the optical layer informationcomprises a load along an optical path.
 19. A system comprising: areconfigurable optical add-drop multiplexer; a router; and asoftware-defined network multi-layer controller communicativelyconnected with the router and the reconfigurable optical add-dropmultiplexer, the software-defined network multi-layer controllercomprising: a processor; and a memory coupled with the processor, thememory storing executable instructions that when executed by theprocessor cause the processor to effectuate operations comprising:obtaining multiple layer information associated with multiple layers ofa telecommunications network, the multiple layer information comprisingoptical layer information and router layer information; based on themultiple layer information, forecasting operation of thetelecommunications network for a plurality of network conditions; andbased on the forecasted operations of the telecommunication network forthe plurality of network conditions, providing a capacity plan optionfor the telecommunications network.
 20. The system of claim 19, whereinthe capacity plan option comprises an addition of a tail.